1. Field of the Invention
This invention relates generally to estimating state of health of an object sensing fusion system and, more particularly, to a method for estimating state of health of an object sensing fusion system in which target data from two or more object sensors with an overlapping field of view are analyzed to determine target correlation matching scores, where the matching scores are calculated both within individual frames of data and across a sequence of frames.
2. Discussion of the Related Art
Object detection systems, also known as object sensing systems, have become increasingly common in modern vehicles. Object detection systems can provide a warning to a driver about an object in the path of a vehicle. Object detection systems can also provide input to active vehicle systems—such as Adaptive Cruise Control, which controls vehicle speed to maintain appropriate longitudinal spacing to a leading vehicle, and Collision Avoidance systems, which can control both steering and braking to attempt to avoid an imminent collision.
Object detection systems use one or more sensors, which may be radar, lidar, camera, or other technologies, to detect the presence of an object in or near the path of a host vehicle. Software is used to track the relative motion of objects over time, determine if the objects are moving or stationary, determine what each object is likely to be (another vehicle, a pedestrian, a tree, etc.), and determine whether each object poses a collision threat to the host vehicle.
Object sensing fusion systems are also known in the art, where the fusion system performs a fusion calculation on target data from two or more sensors, and provides a more robust assessment of in-path objects as a result. However, even with an object sensing fusion system, it is possible for accuracy to suffer if a sensor fails, or if a sensor is partially or completely obscured by dirt or debris, or if a sensor is blinded by direct sun or other light. It would be advantageous to have an assessment of the state of health of the object sensing fusion system, and an indication of possible faulty sensors if the state of health is low.